Author URLs
Document Type
Article
Publication Date
2018
Subject: LCSH
Marine terminals--environmental aspects, Marine terminals--evaluation, Harbors, Shipping, Benchmarking (Management)
Disciplines
Industrial Engineering | Mechanical Engineering
Abstract
This study provides step-wise benchmarking practices of each port to enhance the environmental performance using a joint application of the data-mining technique referred to as Kohonen’s self-organizing map (KSOM) and recursive data envelopment analysis (RDEA) to address the limitation of the conventional data envelopment analysis. A sample of 20 container ports in the U.S.A. were selected, and data on input variables (number of quay crane, acres, berth and depth) and output variables (number of calls, throughput and deadweight tonnage, and CO2 emissions) are used for data analysis. Among the selected samples, eight container ports are found to be environmentally inefficient. However, there appears to be a high potential to become environmentally efficient ports. In conclusion, it can be inferred that the step-wise benchmarking process using two combined methodologies substantiates that a more applicable benchmarking target set of decision-making units is be projected, which consider the similarity of the physical and operational characteristics of homogenous ports for improving environmental efficiency.
DOI
10.1080/13675567.2018.1504903
Repository Citation
Park, Yong Shin; Ghani, N. Muhammad Aslaam Mohamed Abdul; Gebremikael, Fesseha; and Egilmez, Gokhan, "Benchmarking Environmental Efficiency of Ports Using Data Mining and RDEA: The Case of a U.S. Container Ports" (2018). Mechanical and Industrial Engineering Faculty Publications. 41.
https://digitalcommons.newhaven.edu/mechanicalengineering-facpubs/41
Publisher Citation
Yong Shin Park, N. Muhammad Aslaam Mohamed Abdul Ghani, Fesseha Gebremikael & Gokhan Egilmez (2019) Benchmarking environmental efficiency of ports using data mining and RDEA: the case of a U.S. container ports, International Journal of Logistics Research and Applications, 22:2, 172-187, doi: 10.1080/13675567.2018.1504903
Comments
This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Logistics Research and Applications on August 6, 2018, available online: http://www.tandfonline.com/doi/full/10.1080/13675567.2018.1504903